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5 CONSTRAINT SATISFACTION PROBLEMS

5 CONSTRAINTSATISFACTIONPROBLEMSI nwhich weseehowtreatingstatesasmore thanjustlittleblack boxesleadsto theinventionofa range ofpowerfulnew search methodsanda deeperunderstandingofproblemstructure and4 exploredtheideathatproblemscanbesolvedby searchinginaspaceofstates. Thesestatescanbeevaluatedbydomain-specif icheuristicsandtestedtoseewhetherthey ,however,eachstateis is representedbyanarbi-BLACKBOX trarydatastructurethatcanbeaccessedonlyb ytheproblem-specificroutines thesuccessorfunction,heuristicfunction, , whosestatesandgoaltestconformtoa standard,structured,andverysimplereprese ntation( ).Searchal-REPRESENTATION gorithmscanbedefinedthattake advantageofthestructureofstatesandusegen eral-purposeratherthanproblem-specifiche uristicsto enablethesolutionoflargeproblems( ).

indicating which solutions are preferred. For example, in a university timetabling problem, Prof. X might prefer teaching in the morning whereas Prof. Y prefers teaching in the after-noon. A timetable that has Prof. X teaching at 2 p.m. would still be a solution (unless Prof. X happens to be the department chair), but would not be an optimal one.

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INTRODUCTION

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